In literature, all these HSI representations are widely exploited for HSIC. Most of the DNNs for pixel-wise classification utilized the spectral representation of HSIs [1]}, [2]}. However, to mitigate the limitations of spectral representation, many efforts have been made to incorporate the spatial information [3]}, [4]}. Recently, joint exploitation of both spectral and spatial features has gained much popularity and led to improved classification accuracy [5]}, [6]}, [7]}, [8]}, [9]}, [10]}. These HSI feature exploitation approaches, for HSIC, are further discussed in the following sections.
